Self-regulated profiles and academic achievement.
To date, research on the relation between learning self-regulation and academic achievement has generally show disparate results. This work intends to look into this relation from a new perspective, which consists in classifying the students as more or less self-regulated depending on diverse indicators and using cluster analysis. The aim of this work was to identify the possible self-regulated learning profiles in a sample of university students. By means of stepwise linear regression analysis, we determined which of the selected variables better predicted metacognitive self-regulation. Then, three significantly different self-regulated learning profiles were obtained by two-step cluster analysis with those variables. Lastly, ANOVA was used to analyse the relation between the self-regulated learning profiles and academic achievement. The implications of these data for the educational practice at university are discussed.
Valle
Antonio
A
Facultad de Ciencias de la Educación, University of A Coruña, A Coruña, Spain. vallar@udc.es
Núñez
José Carlos
JC
Cabanach
Ramón G
RG
González-Pienda
Julio Antonio
JA
Rodríguez
Susana
S
Rosário
Pedro
P
Cerezo
Rebeca
R
Muñoz-Cadavid
María A
MA
D000124:Achievement; D005260:Female; D006801:Humans; D007858:Learning; D008297:Male; D009042:Motivation; D012927:Social Control, Informal; D011795:Surveys and Questionnaires